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Machine Learning Tutorials
(w/ Python)

1- Linear Regression

Linear Regression Tutorials, Examples and Tips

2- Logistic Regression

Logistic Regression Tutorials and Examples

3- kNN

k Nearest Neighbor tutorial with explanation and examples

4- Naive Bayes

Naive Bayes Tutorials and Examples

5- Decision Trees

Decision Tree Tutorials & Examples

6- Random Forest

Random Forest tutorials, code example, explanation and tips and tricks

7- SVM

Support Vector Machines Tutorials, Tips, Examples

AI and Machine Learning are more popular than ever. Implementations of these technologies aren’t going anywhere instead they are being more and more utilized. Depending on the perspective it can be an endless discussion of theory, mathematics, physics, sociology, philosophy, theology and even politics.

It can also be a practical technology that you can start using today.

I made these practical guides about different ML Algorithms in case there are people like me who like to mix top-down and bottom-up approaches when it comes to learning something new.

Each tutorial starts with a top-down, no non-sense approach and outright implementations, then some advanced knowledge… 

The aim is to help as many people as possible to get familiar, use each algorithm for their own benefit or humanity in least possible time.

We all need someone to hold our bicycle the first time side-wheels are removed. After that, it’s up to you to wander as far as you’d like and discover as much as you’d like and as often as you’d like.

I hope you will jump on the Machine Learning bicycle every single day and discover amazing things.

Best way to shut down noise is to play your own music! The advice of professionals, academia, service providers, salesman etc. usually doesn’t apply to 

Learn and discover as much as you’d like and create your own dreams and come up with your own style.

We hope you like it. Good luck and Enjoy!

HolyPython Team